Frequency-based decoupling and finite element model updating in vibration of cable–beam systems

Abstract

Interactions between cable and structure affect the modal properties of cabled structures such as overhead electricity transmission and distribution line systems. Modal properties of a single in-service pole are difficult to determine. A frequency response function of a pole impacted with a modal hammer will contain information about not only the pole but also the conductors and adjacent poles connected thereby. This article presents a generally applicable method to extract modal properties of a single structural element, within an interacting system of cables and structures, with particular application to electricity poles. A scalable experimental lab-scale pole-line consisting of a cantilever beam and stranded cable and a more complex system consisting of three cantilever beams and a stranded cable are used to validate the method. The frequency response function of a cantilever (“pole”) is predicted by substructural decoupling of measured cable dynamics (known frequency response function matrix) from the measured response of the assembled cable–beam system (known frequency response function matrix). Various amounts of sag can be present in the cable. Comparison of the estimated and directly obtained pole frequency response functions show good agreement, demonstrating that the method can be used in cabled structures to obtain modal properties of an individual structural element with the effects of cables and adjacent structural elements filtered out. A frequency response function–based finite element model updating is then proposed to overcome the practical limitation of accessing some components of the real-world system for mounting sensors. Frequency response functions corresponding to inaccessible points are generated based on the measured frequency response functions corresponding to accessible points. The results verify that the frequency response function–based finite element model updating can be used for substructural decoupling of systems in which some essential points, such as coupling points, are inaccessible for direct frequency response function measurement.

Modal parameter calculation and vibration characteristic analysis of transmission line conductor

“…Modal parameters can characterize the health state of conductors, which include natural frequency, damping ratio, and modal vibration shape [1]. As a result, in the field of health monitoring, the modal parameter identification method, which extracts structural features from response signals, plays an important role [2][3][4][5].…”

A Rolling Bearing Fault Diagnosis Method via 2D Feature Map of CSCoh After Denoising and MSCNN Under Different Conditions

“…At present, deep learning has been applied in fault diagnosis due to its full application and verification in various fields such as image, medical treatment, and decision making. Typical deep learning models include deep belief network (Zhao, et al, 2022), convolutional neural network (Jalali and Rideout, 2021), and generative adversarial networks (Goodfellow, et al, 2014). The CNN-based model adopts the method of sharing weights, which reduces the number of training parameters, to efficiently extract high-dimensional features.…”

An ED-PSO model updating algorithm for structure health monitoring of beam-like structures

“…Currently, there has been a lot of research on finite element model updating. Carvalho [8] et al have successfully applied the optimal matrix method model updating technology to model updating of incomplete measured modal data. Wang [9] et al obtained good updating results by updating the model of a bridge and using the elastic modulus of concrete and steel bars of the bridge as updating parameters.Guvenc Canbaloglu [10] et al completed model updating of nonlinear structures by testing the frequency response function of nonlinear structures, and achieved good results.…”